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LLM ComparisonGPT-5.5Claude 4.5 Opus

GPT-5.5 vs Claude 4.5 Opus

Compare GPT-5.5 and Claude 4.5 Opus. Build AI products powered by either model on Appaca.

Model Comparison

FeatureGPT-5.5Claude 4.5 Opus
ProviderOpenAIAnthropic
Model Typetexttext
Context Window1,000,000 tokens200,000 tokens
Input Cost
$5.00/ 1M tokens
$5.00/ 1M tokens
Output Cost
$30.00/ 1M tokens
$25.00/ 1M tokens

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Strengths & Best Use Cases

GPT-5.5

OpenAI

1. Strongest Agentic Coding Model

  • State-of-the-art on Terminal-Bench 2.0 (82.7%), Expert-SWE (73.1%), and SWE-Bench Pro (58.6%), outperforming GPT-5.4 on complex coding tasks.
  • Holds context across large systems, reasons through ambiguous failures, and carries changes through surrounding codebases with fewer tokens.

2. Higher Intelligence at GPT-5.4 Latency

  • Co-designed, trained, and served on NVIDIA GB200/GB300 NVL72 systems to match GPT-5.4 per-token latency while performing at a significantly higher level.
  • Uses fewer tokens to complete the same tasks, making it more efficient as well as more capable.

3. Powerful for Knowledge Work & Computer Use

  • Scores 84.9% on GDPval (44 occupations) and 78.7% on OSWorld-Verified for autonomous computer operation.
  • Excels at generating documents, spreadsheets, and reports; naturally moves across finding information, using tools, and checking output.

4. Scientific Research Co-Scientist

  • Leading performance on GeneBench, BixBench, and FrontierMath; helped discover a new proof about Ramsey numbers verified in Lean.
  • Strong enough to meaningfully accelerate progress at the frontiers of biomedical and mathematical research.

Claude 4.5 Opus

Anthropic

1. Maximum capability with more practical pricing

  • Anthropic introduced Opus 4.5 as its most intelligent model, combining maximum capability with practical performance.
  • It was positioned as the best model in the world for coding, agents, and computer use at launch, with pricing reduced to $5/M input and $25/M output.

2. Step-change gains for coding and advanced agent work

  • Anthropic describes Opus 4.5 as state-of-the-art on real-world software engineering tests.
  • It also improved everyday knowledge-work tasks like deep research, slides, and spreadsheets while staying strong on long-horizon agent workflows.

3. Better control over reasoning depth

  • Opus 4.5 introduced the effort parameter, letting developers trade off response thoroughness against token efficiency.
  • This made it easier to use one flagship model across both high-depth analysis and more cost-sensitive production workloads.

4. Stronger computer use and continuity

  • Added enhanced computer use with a zoom action for inspecting detailed screen regions.
  • Preserves prior thinking blocks across turns, helping the model maintain reasoning continuity in extended multi-step tasks.

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